On Transients, Lyapunov Functions and Turing Instabilities

Motivated by the papers [84, 85], this thesis considers the concepts of reactivity, Lyapunov stability and Turing patterns. We introduce the notion of P-reactivity, a new measure for transient dynamics. We extend a result by Shorten and Narendra [108] regarding joint dissipativity for second order systems. We derive an easy verifiable formula that determines systems P-reactivity with respect to a norm induced by the positive definite matrix P. An optimization problem aiming to determine the positive definite P with respect to which a stable system is most reactive is posed and solved numerically for second order systems. The stability radius is adopted as a measure of robustness of joint disspaptivity. We characterise the stability radius of joint dissipativity when the underlying systems are subject to certain specific perturbation structures. A detailed robustness analysis of the Shorten and Narendra conditions is also presented. Using the notion of common Lyapunov function we show that the necessary condition in [85] is a special case of a more powerful (i.e tighter) necessary condition. Specifically, we show that if the linearised reaction matrix and the diffusion matrix share a common Lyapunov function, then Turing instability is not possible. The existence of common Lyapunov functions is readily checked using semi-definite programming. We also further extend this to include more complicated movement mechanisms such as chemotaxis. Unlike the traditional techniques, this new necessary condition can be used to check Turing instability for systems with any dimension and any number of parameters. We apply our new conditions to various models in literature

Shared inputs, entrainment, and desynchrony in elliptic bursters: from slow passage to discontinuous circle maps

What input signals will lead to synchrony vs. desynchrony in a group of biological oscillators? This question connects with both classical dynamical systems analyses of entrainment and phase locking and with emerging studies of stimulation patterns for controlling neural network activity. Here, we focus on the response of a population of uncoupled, elliptically bursting neurons to a common pulsatile input. We extend a phase reduction from the literature to capture inputs of varied strength, leading to a circle map with discontinuities of various orders. In a combined analytical and numerical approach, we apply our results to both a normal form model for elliptic bursting and to a biophysically-based neuron model from the basal ganglia. We find that, depending on the period and amplitude of inputs, the response can either appear chaotic (with provably positive Lyaponov exponent for the associated circle maps), or periodic with a broad range of phase-locked periods. Throughout, we discuss the critical underlying mechanisms, including slow-passage effects through Hopf bifurcation, the role and origin of discontinuities, and the impact of noiseComment: 17 figures, 40 page

Dissipative, Entropy-Production Systems across Condensed Matter and Interdisciplinary Classical VS. Quantum Physics

The thematic range of this book is wide and can loosely be described as polydispersive. Figuratively, it resembles a polynuclear path of yielding (poly)crystals. Such path can be taken when looking at it from the first side. However, a closer inspection of the book’s contents gives rise to a much more monodispersive/single-crystal and compacted (than crudely expected) picture of the book’s contents presented to a potential reader. Namely, all contributions collected can be united under the common denominator of maximum-entropy and entropy production principles experienced by both classical and quantum systems in (non)equilibrium conditions. The proposed order of presenting the material commences with properly subordinated classical systems (seven contributions) and ends up with three remaining quantum systems, presented by the chapters’ authors. The overarching editorial makes the presentation of the wide-range material self-contained and compact, irrespective of whether comprehending it from classical or quantum physical viewpoints

Spectrum analysis of LTI continuous-time systems with constant delays: A literature overview of some recent results

In recent decades, increasingly intensive research attention has been given to dynamical systems containing delays and those affected by the after-effect phenomenon. Such research covers a wide range of human activities and the solutions of related engineering problems often require interdisciplinary cooperation. The knowledge of the spectrum of these so-called time-delay systems (TDSs) is very crucial for the analysis of their dynamical properties, especially stability, periodicity, and dumping effect. A great volume of mathematical methods and techniques to analyze the spectrum of the TDSs have been developed and further applied in the most recent times. Although a broad family of nonlinear, stochastic, sampled-data, time-variant or time-varying-delay systems has been considered, the study of the most fundamental continuous linear time-invariant (LTI) TDSs with fixed delays is still the dominant research direction with ever-increasing new results and novel applications. This paper is primarily aimed at a (systematic) literature overview of recent (mostly published between 2013 to 2017) advances regarding the spectrum analysis of the LTI-TDSs. Specifically, a total of 137 collected articles-which are most closely related to the research area-are eventually reviewed. There are two main objectives of this review paper: First, to provide the reader with a detailed literature survey on the selected recent results on the topic and Second, to suggest possible future research directions to be tackled by scientists and engineers in the field. © 2013 IEEE.MSMT-7778/2014, FEDER, European Regional Development Fund; LO1303, FEDER, European Regional Development Fund; CZ.1.05/2.1.00/19.0376, FEDER, European Regional Development FundEuropean Regional Development Fund through the Project CEBIA-Tech Instrumentation [CZ.1.05/2.1.00/19.0376]; National Sustainability Program Project [LO1303 (MSMT-7778/2014)

Mathematical Approaches to Understanding Mammalian Circadian Rhythms

Nearly all life on earth exists in a periodic environment, in which important factors like sunlight and temperature change predictably with a twenty-four hour cycle. As a process which only reacts to the current state of a periodic signal will constantly suffer a phase lag, organisms have developed a natural feedforward controller to predict upcoming environmental changes. Such a system allows an organism to align their behavior to the correct phase of the day/night cycle and ease transitions between times of energy abundance and energy scarcity. These daily changes in physiology are known as circadian rhythms and are coordinated by intricate genetic regulatory networks.Over evolutionary timescales, nearly all aspects of gene expression have been coupled to the day/night cycle. As a result, circadian rhythms are essential to maintaining metabolic homeostasis, DNA repair, cell cycling, and other important cellular processes. Since modern societies have deviated from their evolutionary prescribed sleep and feeding schedules, disturbances to circadian gene expression have grown more common. Beyond acute effects on performance and fatigue, compromised circadian rhythms have been linked to chronic issues such as the onset of metabolic disease or increased cancer risk. Since circadian rhythms can be damped by factors such as jet lag, shift work, and high fat diets, there has been recent interest in developing pharmacological or behavioral therapies which might restore normal circadian rhythms.This thesis uses techniques from dynamic systems to model circadian oscillations at different scales. First, a mathematical model of the core circadian feedback loop is developed in order to explain a novel small molecule modulator, KL001. Through this mathematical model, we gain new insight into how the two isoforms of cryptochrome (CRY1 and CRY2) interact to control the period. The identifiability of parameters and parametric sensitivities in oscillatory models is investigated next, and a dynamic optimization technique using collocation methods and nonlinear programming is shown to be able to efficiently bootstrap confidence intervals in such parameters. This technique is then applied to a set of three circadian models in order to identify mechanisms which are able to differentiate between the effect of two small molecule regulators, even across differences in parameter values and kinetic assumptions. Next, the effect of finite-duration perturbations on clock amplitude and synchrony is explored. New techniques and sensitivity analyses are developed which allow the effect of transient perturbations on the clock to be efficiently calculated without the need for computationally intensive stochastic simulations. Finally, the effect of clock perturbations on stochastic noise is investigated by fitting the damping rate of cultured cellular reporters. Using genome-wide siRNA knockdown screens, we are able to gain fundamental insight into design principles of circadian oscillations

Algorithms and Software for Biological MP Modeling by Statistical and Optimization Techniques

I sistemi biologici sono gruppi di entit\ue0 biologiche (es. molecole ed organismi), che interagiscono producendo specifiche dinamiche. Questi sistemi sono solitamente caratterizzati da una elevata complessit\ue0 perch\ue8 coinvolgono un elevato numero di componenti con molte interconnessioni. La comprensione dei meccanismi che governano i sistemi biologici e la previsione dei loro comportamenti in condizioni normali e patologiche \ue8 una sfida cruciale della biologia dei sistemi (in inglese detta systems biology), un'area di ricerca al confine tra biologia, medicina, matematica ed informatica. In questa tesi i P sistemi metabolici, detti brevemente sistemi MP, sono stati utilizzati come modello discreto per l'analisi di dinamiche biologiche. Essi sono una classe deterministica dei P sistemi classici, che utilizzano regole di riscrittura per rappresentare le reazioni chimiche e "funzioni di regolazioni di flusso" per regolare la reattivit\ue0 di ciascuna reazione rispetto alla quantita' di sostanze presenti istantaneamente nel sistema. Dopo un excursus sulla letteratura relativa ad alcuni modelli convenzionali (come le equazioni differenziali ed i modelli stocastici proposti da Gillespie) e non-convenzionali (come i P sistemi ed i P sistemi metabolici), saranno presentati i risultati della mia ricerca. Essi riguardano tre argomenti principali: i) l'equivalenza tra sistemi MP e reti di Petri ibride funzionali, ii) le prospettive statistiche e di ottimizzazione nella generazione di sistemi MP a partire da dati sperimentali, iii) lo sviluppo di un laboratorio virtuale chiamato MetaPlab, un software Java basato sui sistemi MP. L'equivalenza tra i sistemi MP e le reti di Petri ibride funzionali \ue8 stata dimostrata per mezzo di due teoremi ed alcuni esperimenti al computer per il caso di studio del meccanismo regolativo del gene operone lac nella pathway glicolitica. Il secondo argomento di ricerca concerne nuovi approcci per la sintesi delle funzioni di regolazione di flusso. La regressione stepwise e le reti neurali sono state impiegate come approssimatori di funzioni, mentre algoritmi di ottimizzazione classici ed evolutivi (es. backpropagation, algoritmi genetici, particle swarm optimization ed algoritmi memetici) sono stati impiegati per l'addestramento dei modelli. Una completo workflow per l'analisi dei dati sperimentali \ue8 stato presentato. Esso gestisce ed indirizza l'intero processo di sintesi delle funzioni di regolazione, dalla preparazione dei dati alla selezione delle variabili, fino alla generazione dei modelli ed alla loro validazione. Le metodologie proposte sono state testate con successo tramite esperimenti al computer sui casi di studio dell'oscillatore mitotico negli embrioni anfibi e del non photochemical quenching (NPQ). L'ultimo tema di ricerca \ue8 infine piu' applicativo e riguarda la progettazione e lo sviluppo di una architettura Java basata su plugin e di una serie di plugin che consentono di automatizzare varie fasi del processo di modellazione con sistemi MP, come la simulazione di dinamiche, la determinazione dei flussi e la generazione delle funzioni di regolazione.Biological systems are groups of biological entities, (e.g., molecules and organisms), that interact together producing specific dynamics. These systems are usually characterized by a high complexity, since they involve a large number of components having many interconnections. Understanding biological system mechanisms, and predicting their behaviors in normal and pathological conditions is a crucial challenge in systems biology, which is a central research area on the border among biology, medicine, mathematics and computer science. In this thesis metabolic P systems, also called MP systems, have been employed as discrete modeling framework for the analysis of biological system dynamics. They are a deterministic class of P systems employing rewriting rules to represent chemical reactions and "flux regulation functions" to tune reactions reactivity according to the amount of substances present in the system. After an excursus on the literature about some conventional (i.e., differential equations, Gillespie's models) and unconventional (i.e., P systems and metabolic P systems) modeling frameworks, the results of my research are presented. They concern three research topics: i) equivalences between MP systems and hybrid functional Petri nets, ii) statistical and optimization perspectives in the generation of MP models from experimental data, iii) development of the virtual laboratory MetaPlab, a Java software based on MP systems. The equivalence between MP systems and hybrid functional Petri nets is proved by two theorems and some in silico experiments for the case study of the lac operon gene regulatory mechanism and glycolytic pathway. The second topic concerns new approaches to the synthesis of flux regulation functions. Stepwise linear regression and neural networks are employed as function approximators, and classical/evolutionary optimization algorithms (e.g., backpropagation, genetic algorithms, particle swarm optimization, memetic algorithms) as learning techniques. A complete pipeline for data analysis is also presented, which addresses the entire process of flux regulation function synthesis, from data preparation to feature selection, model generation and statistical validation. The proposed methodologies have been successfully tested by means of in silico experiments on the mitotic oscillator in early amphibian embryos and the non photochemical quenching (NPQ). The last research topic is more applicative, and pertains the design and development of a Java plugin architecture and several plugins which enable to automatize many tasks related to MP modeling, such as, dynamics computation, flux discovery, and regulation function synthesis

Target patterns and pacemakers in reaction-diffusion systems

Pattern formation in systems far from thermal equilibrium is a fascinating phenomenon. Reaction-diffusion systems are an important type of system where pattern formation is observed. The target pattern and the associated wave source called pacemaker are typical patterns in such systems. This thesis studies pacemakers and target patterns systematically by analytical and numerical means. The underlying dynamics of the system may be oscillatory or excitable and the pacemakers may either consist of spatial heterogeneities of the medium or be self-organized, i.e. result of intrinsic processes. The investigation of heterogeneous pacemakers in oscillatory systems in the framework of the complex Ginzburg-Landau equation focuses on two aspects. First, the conditions of the creation of pacemakers and extended target patterns versus the creation of wave sinks and localized target patterns are derived systematically. In particular, inward traveling target patterns and large heterogeneities are discussed. Then, pacemakers which emit target waves with high frequencies are considered. In this case, the waves become Eckhaus unstable, causing ring-shaped amplitude defects or other complex patterns. For even larger frequencies, the amplitude defects already take place at the boundary of the heterogeneity, giving rise to a localized desynchronization phenomenon. Moreover, wave sinks can have a significant impact on the spatio-temporal dynamics of the system by breaking the waves arriving from other wave sources. It is well known that oscillatory media close to a Hopf bifurcation are not able to give rise to stable self-organized pacemakers. Therefore, to model such pacemakers, a system close to a pitchfork-Hopf bifurcation is proposed. The normal form and amplitude equations of the pitchfork-Hopf bifurcation are derived. Such a system displays birhythmicity, i.e. bistability of limit cycles, and it is demonstrated analytically that stable self-organized pacemakers are possible. Simulations confirm the existence of stable self-organized pacemakers. In the presence of a parameter gradient, such patterns drift, as shown analytically and numerically. The interaction between pacemakers is studied numerically, giving rise either to coexisting pacemakers or to a new phenomenon called global inhibition: Established pacemakers suppress new cores or merge with them. When the frequencies of the limit cycles differ strongly, the waves may become Eckhaus unstable and the pacemaker may destabilize. Furthermore, kinetic instabilities of the pacemakers are possible, creating breathing and swinging pacemakers. Self-organized pacemakers in excitable media are usually unstable. In this thesis, a three-component activator-inhibitor system on the basis of the FitzHugh-Nagumo model is proposed that gives rise to stable self-organized pacemakers in the excitable regime. The formation of such patterns is demonstrated if several conditions are fulfilled: The system is close to relaxational oscillations, the additional component is strongly diffusive, and the additional component inhibits the inhibitor. Moreover, bistability of pulse solutions is observed in such a system. Different pulses can interact and may create pacemakers. Alternatively, other complex spatio-temporal dynamics is observed. If the diffusion of the activator vanishes, the waves emitted by the wave source are unstable and spatio-temporal chaos appears. Thus, this thesis presents new results on the dynamics of pacemakers with large frequencies and demonstrates for the first time the possibility of stable self-organized pacemakers in birhythmic and excitable systems